ZipRecruiter

Log In

1

Machine Learning Engineer Python Jobs in Denver, CO

DevIQ

Senior AI/Machine Learning Engineer

Denver, CO · On-site +1

$126K - $166K/yr

We're looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI ... Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.

DevIQ

Senior AI/Machine Learning Engineer

Denver, CO · On-site +1

$126K - $166K/yr

We're looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI ... Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.

AppFolio

Staff Machine Learning Engineer

Denver, CO

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ... Strong Python, Docker, dependency management, and CI/CD for AI workloads. * RAG & agents: Working ...

Cisco

Principal Machine Learning Engineer

Denver, CO · On-site

$291K - $369K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

next page

Showing results 1-20

All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Denver, CO

Machine Learning Engineer Python information

See Denver, CO salary details

$23.7K

$144.1K

$208.4K

How much do machine learning engineer python jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer python in Denver, CO is $144,069.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,700.00 and $169,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is the salary of machine learning engineer in Python?

The average salary for a machine learning engineer proficient in Python typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those requiring specialized skills in deep learning or data engineering may offer higher compensation.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What is the difference between Machine Learning Engineer Python vs Data Scientist?

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What engineer makes $500,000 a year?

A senior or lead machine learning engineer with extensive experience, advanced skills in Python, deep learning, and data modeling can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Such roles often require advanced degrees, certifications, and a strong track record of successful projects.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI director, often involving advanced skills in Python, deep learning, and data science. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in competitive industries like tech or finance.

Is Python enough for ML engineers?

Python is a fundamental programming language for machine learning engineers due to its extensive libraries like TensorFlow, PyTorch, and scikit-learn. However, proficiency in data manipulation, algorithms, and understanding of machine learning concepts, along with knowledge of tools like SQL and cloud platforms, are also important for success in the role.
What are popular job titles related to Machine Learning Engineer Python jobs in Denver, CO? For Machine Learning Engineer Python jobs in Denver, CO, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Denver, CO look for? The top searched job categories for Machine Learning Engineer Python jobs in Denver, CO are:
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Denver, CO as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $144,069 per year, or $69.3 per hour.
Machine Learning / Data Science Engineer

Machine Learning / Data Science Engineer

CapTech Consulting

Denver, CO • On-site

$117K - $141K/yr

Full-time

Medical, Retirement, PTO

Re-posted 20 days ago

Job description

Company Description
CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
Job Description
CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
Specific responsibilities for the Machine Learning Engineer position include:
  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.

Qualifications
  • Bachelor's degree or equivalent combination of education and experience.
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  • Strong understanding of conversational UX and prompt evaluation metrics
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration

Additional Information
We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs.
  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  • Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
  • Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities.
  • 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness - each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
CapTech supports Equal Pay for all. In addition, in the State of Colorado, we are committed to Equal Pay for ALL in accordance with the Colorado Equal Pay for Equal Work Act. The base pay range for this role is: $95,000 - $200,000.
At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.

Apply